CMRT09

Stilla, Uwe

Bibliographic data

Monograph

Persistent identifier:: 856955019

Author:: Stilla, Uwe

Title:: CMRT09

Sub title:: object extraction for 3D city models, road databases, and traffic monitoring ; concepts, algorithms and evaluation ; Paris, France, September 3 - 4, 2009 ; [joint conference of ISPRS working groups III/4 and III/5]

Scope:: X, 234 Seiten

Year of publication:: 2009

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856955019

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: TRAJECTORY-BASED SCENE DESCRIPTION AND CLASSIFICATION BY ANALYTICAL FUNCTIONS D. Pfeiffer, R. Reulke

Document type:: Monograph

Structure type:: Chapter

CMRT09: Object Extraction for 3D City Models, Road Databases and Traffic Monitoring - Concepts, Algorithms, and Evaluation 46 Table 3. Comparison of results for hyperbolas fits achieved by Coboid and KNN-Classifier Figure 7 shows a clear separation of the feature space. A high classification rate is achieved by both elementary classifiers (see table 3). 5. CONCLUSION AND OUTLOOK Table 3 affirms a high reliability on these elementary func tions, with respect to the used basic classification methods. Mistakes within the classification mostly reside due to scene behaviour that occurs fairly rare (e.g. car turning at the inter section) or is not modelled by the underlying functions (e.g. pedestrians or cyclists crossing in very custom patterns). The shown approaches have been tested and verified in a real time environment with a multi-camera system. The system shall to automatically observe the traffic on crossroads in future. For example source-destination depend ences can be determined with that. 6. REFERENCES Anderson, B. and J. Moor (1979). Optimal filtering. Enle- wood Cliffs, New Jersey, Prentice-Hall, Inc. Beynon, M. D., D. J. V. Hook, et al. (2003). Detecting Aban doned Packages in a Multi-Camera Video Surveillance Sys tem. IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'03). Brown, D. C. (1971). "Close range camera calibration." Pho- togrammetric Engineering 37(8): 12. Fitzgibbon, A., M. Pilu, et al. (1999). "Direct least square fitting of ellipses." Pattern Analysis and Machine Intelli gence, IEEE Transactions on 21(5): 476-480. Fitzgibbon, A. W., M. Pilu, et al. (1996). Direct least squares fitting of ellipses. Pattern Recognition, 1996., Proceedings of the 13th International Conference on. Forbes, A. B. (1989). Least-squares best fit geometric ele ments, National Physical Laboratory of Great Britain. Harker, M., P. O'Leary, et al. (2008). "Direct type-specific conic fitting and eigenvalue bias correction." Image Vision Comput 26(3): 372-381. Harlow, C. and Y. Wang (2001). "Automated Accident De tection System." Transportation Research Record 1746(-1): 90-93. Kastrinaki, V., M. Zervakis, et al. (2003). "A survey of video processing techniques for traffic applications." Image and Vision Computing 21(4): 359-381. Kumar, P., S. Ranganath, et al. (2005). "Framework for real time behavior interpretation from traffic video." Intelligent Transportation Systems, IEEE Transactions on 6(1): 43-53. Leykin , A. and M. Tuceryan (2005). A Vision System for Automated Customer Tracking for Marketing Analysis: Low Level Feature Extraction. International Workshop on Human Activity Recognition and Modelling. Oxford, UK. Liscano, R. and D.Green (1989). Design and implementation of a trajectory generator for an indoor mobile robot. Proceed ings of the IEEE/RJS International Conference on Intelligent Robots and Systems. Tsukuba, Japan: 380-385. Luhmann, T. (2006). "Close Range Photogrammetry: Princi ples, Methods and Applications." Michalopoulos, P. G. (1991). "Vehicle detection video through image processing: the Autoscope system." Vehicular Technology, IEEE Transactions on 40( 1): 21 -29. Nelson, W. L. (1989). "Continuous steering-function control of robot carts." IEEE Transactions on Industrial Electronics 36(3): 330-337. Reichardt, D. (1995). A Real-time Approach to Traffic Situa tion Representation from Image Processing Data. Intelligent Vehicles Symposium. Detroit, MI, USA. Reulke, R., S. Bauer, et al. (2008a). Multi-Camera Detection and Multi-Target Tracking. VISAPP 2008. Funchal, Madeira (Portugal). Reulke, R., S. Bauer, et al. (2008b). Situation Analysis and Atypical Event Detection with Multiple Cameras and Multi- Object Tracking. Robot Vision. Auckland (New Zeeland), Springer-Verlag Berlin Heidelberg. Setchell, C. and E. L. Dagless (2001). "Vision-based road- traffic monitoring sensor." Vision, Image and Signal Process ing, IEE Proceedings - 148(1): 78-84. Wei, C.-H., C.-C. Chang, et al. (1996). "Vehicle Classifica tion Using Advanced Technologies." Transportation Re search Record 1551(-1): 45-50. Wigan, M. R. (1992). "Image-Processing Techniques Ap plied to Road Problems." Journal of Transportation Engineer- jng 118(1): 21. Yung, N. H. C. and A. H. S. Lai (2001). "An effective video analysis method for detecting red light runners." Vehicular Technology, IEEE Transactions on 50(4): 1074-1084.

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